2026-09-19T08:52:36Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/331582022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Marija D. Ilić.
Gözüm, Özge Nadia, 1979-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2006-06-20T12:51:45Z
2006-06-20T12:51:45Z
2001
2001
http://hdl.handle.net/1721.1/33158
49217718
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (leaves 104-107).
For a deregulated electricity industry, we consider a general electricity market structure with both long-term bilateral agreements and short-term spot market such that the system users can hedge the volatility of the real-time market. From a Transmission Service Provider's point of view, optimal transmission resource allocation between these two markets poses a very interesting decision making problem for a defined performance criteria under uncertainties. In this thesis, the decision-making is posed as a stochastic dynamic programming problem, and through simulations the strength of this method is demonstrated. This resource allocation problem is first posed as a centrally coordinated dynamic programming problem, computed by one entity at a system- wide level. This problem is shown to be, under certain assumptions, solvable in a deterministic setup. However, implementation for a large transmission system requires the algorithm to handle stochastic inputs and stochastic cost functions. It is observed that the curse of dimensionality makes this centralized optimization infeasible. Thesis offers certain remedies to the computational issues, but motivates a partially distributed setup and related optimization functions for a better decision making in large networks where the intelligent system users drive the use of network resources. Formulations are introduced to reflect mathematical and policy constraints that are crucial to distributed network operations in power systems.
by Özge Nadia Gözüm.
M.Eng.
107 leaves
465027 bytes
464470 bytes
application/pdf
application/pdf
eng
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Decision tools for electricity transmission service and pricing : a dynamic programming approach
Thesis
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